Probabilistic Optimization of a Nordic Smart Local Energy System: Cost and Emission Insights From 2020 to 2023

Abstract

Smart local energy systems (SLESs) are central to enhancing localization and decentralization of the energy sector. Although these systems are widely studied in literature, Nordic conditions and probabilistic approaches have remained out of the spotlight. This study analyzes economically optimized configurations for a Nordic SLES. We define the cost levels at which various technologies become feasible to invest in. We also evaluate the life cycle emission reductions achievable from these systems. Our case study utilizes Monte Carlo optimization with integrated economic and emission models. The results of the 2000 cost-optimized SLES configurations for the years 2020–2023 indicated that compared to the baseline, the levelized cost of electricity reduced in 98% of the cases, while the specific greenhouse gas emissions reduced in 97% of the cases. The mean positive carbon handprint was 44%. Maximum costs to deploy technologies were 30 €/MWh for wind power, 500 €/kW for solar power, and 120 €/kWh for battery storage. Thermal energy storage was commonly utilized. The outcomes highlight the importance of sector integration in the context of SLESs, as the optimized cases achieved large emission reductions especially in the heat carrier. The results indicate that Nordic SLESs could be economically viable for emission mitigation.